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YouTube Videos I want to try to implement!

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction

    News: 2025-07-26



    Date: 07/26/2025

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    I spent some time testing the new ChatGPT Agent, which is now available to all Plus subscribers. My goal was to see if it could handle the kind of multi-step, real-world tasks we often build complex automations for. I challenged it with everything from researching products and comparing travel options to compiling content for a newsletter.

    The agent shows a fascinating glimpse into the future of autonomous workflows, successfully navigating multiple browser tabs and synthesizing information from a single prompt. However, it’s still very much a first version, with noticeable quirks and limitations you need to be aware of. For anyone building with no-code tools, this is a must-watch to understand where AI agents are today and where they’re heading.

  • Qwen 3 2507: NEW Opensource LLM KING! NEW CODER! Beats Opus 4, Kimi K2, and GPT-4.1 (Fully Tested)

    News: 2025-07-26



    Date: 07/26/2025

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    Alibaba just dropped a new open-source model, Qwen 3-235B, and it’s a game changer for those of us who need high-performance AI without the closed-source limitations. I’m gonna dive into why this model is a serious contender, comparing it directly to the likes of GPT-4.1 and Claude Opus, which are still behind paywalls.

    If you’re working with no-code or low-code tools, you’ll appreciate the model’s agentic skills. It can reason, plan, and use tools, which means you can build more sophisticated automations. Plus, the massive 256K context window? That’s a whole new level for workflows that need to handle large amounts of information.

    This isn’t just another update; it’s a robust new tool that brings state-of-the-art capabilities within reach of more creators and small teams.

  • We made Supabase Auth way faster!

    News: 2025-07-26



    Date: 07/26/2025

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    I’ve always been wary of the performance hit that comes with server-side authentication. Each check can mean a slow network round-trip, which really adds up. But with Supabase’s new JWT Signing Keys, everything changes. Now, you can validate user sessions locally within your own application. This is a huge performance win! It eliminates that auth-related network latency, making for a much snappier user experience. It’s a great example of a modern, edge-friendly solution to a common bottleneck that typically slows down our apps.

    To see this in action, check out the video by Jon Meyers. He walks through the entire process, from enabling the feature to refactoring a Next.js app to take full advantage of it.

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction

    News: 2025-07-26



    Date: 07/26/2025

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    OpenAI’s new ChatGPT Agent is finally here, promising to turn a single prompt into a multi-step research and execution plan. This hands-on review tests its capabilities with practical, real-world tasks, from comparing travel options to gathering content for a newsletter. For those of us building structured automations in tools like n8n, this is a fascinating look at a different paradigm: prompt-based automation, where the AI generates the workflow on the fly from a natural language goal. While the results show it’s not without its quirks, the potential for automating complex research is undeniable. It’s an early but exciting glimpse into how we might soon kick off entire projects with just a single sentence.

  • Qwen 3 2507: NEW Opensource LLM KING! NEW CODER! Beats Opus 4, Kimi K2, and GPT-4.1 (Fully Tested)

    News: 2025-07-26



    Date: 07/26/2025

    Watch the Video

    Alibaba just dropped a new open-source model, Qwen 3-235B, and it’s a serious contender for the top spot, even against the closed-source heavyweights. There’s a great video that breaks it all down, comparing it directly to models like GPT-4.1 and Claude Opus. The big takeaway for anyone building with AI is its impressive performance in agentic tasks—think reasoning, planning, and tool use. This is crucial for creating more sophisticated automations.

    The video also dives into its massive 256K context window, which is a game changer for handling complex, multi-step workflows. What I really appreciate is the emphasis on running this model locally or accessing it through free APIs. This opens up the possibility of building powerful custom solutions without being tied to those expensive, proprietary systems.

  • Claude Code Agents: The Feature That Changes Everything



    Date: 07/26/2025

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    Okay, so this video about Claude Code’s new agents feature is seriously exciting for anyone diving into AI-enhanced workflows. Basically, it’s a deep dive into how you can build custom AI agents (think souped-up GPTs) within Claude Code and chain them together to automate complex tasks. The video shows you how to build one from scratch with the dice roller and then it ramps up. I am now using that YouTube outline workflow myself!

    Why is this valuable? Well, for me, the biggest draw is the ability to automate multi-step processes. Instead of just using an LLM for a single task, you’re creating mini-AI workflows that pass information between each other. The video nails the importance of clear descriptions for agents. It’s so true–the more precise you are, the better the agent will perform. This directly translates into real-world scenarios like automating code reviews, generating documentation, or even building CI/CD pipelines where each agent handles a specific stage.

    Honestly, what makes this video worth checking out is the practical, hands-on approach. Seeing the presenter build an agent from scratch and then apply it to something completely outside of coding (like video outlining) is inspiring. It highlights the versatility of these AI tools and hints at the potential for truly transforming how we work. I’m going to explore how I can use these agents to help automate new feature implementations and it will be a game changer.

  • Google Just Released an AI App Builder (No Code)



    Date: 07/25/2025

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    Okay, so this video is packed with exactly the kind of stuff I’ve been geeking out over: rapid AI app development, smarter AI agents, and AI integration within creative workflows. Basically, it’s a rundown of how Google’s Opal lets you whip up mini AI apps using natural language – like, describing an AI thumbnail maker and bam, it exists! Plus, the video dives into how ChatGPT Agents can actually find practical solutions, like scoring cheaper flights (seriously, $1100 savings!). And Adobe Firefly becoming this AI-powered creative hub? Yes, please!

    Why is this gold for a developer transitioning to AI? Because it showcases tangible examples of how we can drastically cut down development time and leverage AI for problem-solving. Imagine automating routine tasks or creating internal tools without writing mountains of code. The idea of building a YouTube-to-blog post converter with Opal in minutes? That’s the kind of automation that could free up serious time for more complex challenges. It’s not about replacing code, it’s about augmenting it.

    What really makes this worth a shot is the sheer speed and accessibility demonstrated. The old way of doing things involved weeks of coding, testing, and debugging. Now, we’re talking about creating functional apps in the time it takes to grab a coffee. This is about rapid prototyping, fast iteration, and empowering anyone to build AI-driven solutions. It’s inspiring and something I will be exploring myself.

  • We made Supabase Auth way faster!



    Date: 07/25/2025

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    Okay, this video on Supabase JWT signing keys is definitely worth checking out, especially if you’re like me and trying to level up your development game with AI and automation. In a nutshell, it shows how to switch your Supabase project to use asymmetric JWTs with signing keys, letting you validate user JWTs client-side instead of hitting the Supabase Auth server every time. The demo uses a Next.js app as an example, refactoring the code to use getClaims instead of getUser and walking through enabling the feature and migrating API keys. It also touches on key rotation and revocation.

    Why is this so relevant for us? Well, imagine you’re building an AI-powered app that relies heavily on user authentication. Validating JWTs server-side becomes a bottleneck, impacting performance. This video provides a clear path to eliminating that bottleneck. We can use this approach not only for web apps but also adapt it for serverless functions or even integrate it into our AI agents to verify user identity and permissions locally. It will help improve performance and reduce dependence on external services, and in turn that will speed up our entire development/deployment cycles.

    What I find particularly exciting is the potential for automation. The video mentions a single command to bootstrap a Next.js app with JWT signing keys. Think about integrating this into your CI/CD pipeline or using an LLM to generate the necessary code snippets for other frameworks. Faster authentication means faster feedback loops for users, and less dependency on external validation. It’s a small change that can yield huge performance and efficiency gains, and that makes it absolutely worth experimenting with.

  • ChatGPT Agent Just Went Public—Here’s My Honest Reaction



    Date: 07/25/2025

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    Okay, this ChatGPT Agent video is a must-watch if you’re trying to figure out how to integrate AI into your development workflow. The presenter puts the new Agent through a real-world gauntlet of tasks—from researching projectors to planning trips and even curating a movie newsletter. It’s a fantastic overview of what’s possible (and what isn’t) with this new tool.

    What makes this so valuable is seeing the ChatGPT Agent tackle problems that many of us face daily. Think about automating research for project requirements, generating initial drafts of documentation, or even scripting out basic user flows. Watching the Agent struggle with some tasks while excelling at others gives you a realistic expectation of what it can do. We could potentially use this for automating API research or generating boilerplate code based on specific requirements.

    What really excites me is the potential for no-code/low-code integrations using the Agent. Imagine feeding it user stories and having it generate a basic prototype in a tool like Bubble or Webflow. The possibilities are endless, but it’s crucial to understand its limitations, which this video clearly highlights. I’m definitely going to experiment with this—if nothing else, to save myself a few hours of tedious research each week!

  • This One Fix Made Our RAG Agents 10x Better (n8n)



    Date: 07/23/2025

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    Okay, so this video is all about turbocharging your RAG (Retrieval Augmented Generation) agents in n8n using a deceptively simple trick: proper markdown chunking. Instead of just splitting text willy-nilly by characters, it guides you on structuring your data by markdown headings before you vectorize it. Turns out, the default settings in n8n can be misleading and cause your chunks to be garbage. It also covers converting various formats like Google Docs, PDFs, and HTML into markdown so that you can process them.

    For someone like me, neck-deep in the AI coding revolution, this is gold. I’ve been wrestling with getting my LLM-powered workflows to produce actually relevant and coherent results. The video highlights how crucial it is to feed your LLMs well-structured information. The markdown chunking approach ensures that the context stays intact, which directly translates to better answers from my AI agents. I can immediately see this applying to things like document summarization, chatbot knowledge bases, and even code generation tasks where preserving the logical structure is paramount. Imagine using this for auto-generating API documentation from a codebase!

    Honestly, the fact that a 10-second fix can dramatically improve RAG performance is incredibly inspiring. It’s a reminder that even in the age of complex AI models, the fundamentals – like data preparation – still reign supreme. I’m definitely diving in and experimenting with this; even if it saves me from one instance of debugging nonsensical LLM output, it’ll be worth it!